D. Andre Norfleet

BioE PhD Defense Presentation

Date and Time: Tuesday, April 18th, 2023, at 1:00 PM

Location: EBB 4029

Zoom Link: https://gatech.zoom.us/j/99728507340?pwd=SzBMTHBlSFFRQnNJS3lyRUtCbVJRZz09

Advisor:

Melissa Kemp, PhD (Biomedical Engineering)

Committee:

Craig Forest, PhD (Mechanical Engineering)

Ravi Kane, PhD (Chemical and Biomolecular Engineering)

Sung Jin Park, PhD (Biomedical Engineering)

Manu Platt, PhD (Biomedical Engineering)

Eberhard Voit, PhD (Biomedical Engineering)

Metabolic and Bioelectric Crosstalk in Directed Differentiation and Spatial Patterning of iPSC-derived Cardiomyocytes

The goal of multi-cellular engineered living systems is the design and manufacturing of multi-cellular systems with novel form or function using engineering design principles. Induced pluripotent stem cells represent an excellent tool to enable actualization of these design goals because of their intrinsic pluripotent capacity and previous recapitulation of various embryogenesis and organogenesis processes. The objective of this research was to investigate through computational modeling how molecular components of bioelectric and metabolic systems alter multicellular bioelectric patterning and cell metabolic flux dynamics, and to this extend system understanding to guide emergent morphogenic outcomes via external modulation of the culturing environment. The central hypothesis of this work was that specific media compositions can alter molecular components of bioelectric and metabolic multicellular systems in a predictable manner, leading to desired morphologies, cell phenotypes, and novel functionalities. In the first study, In multi-scale bioelectric computational model describing human iPSC tissue-scale membrane voltage potentials (Vmem) was developed to understand unexplored patterning outcomes when various molecular components of the bioelectric system are altered by culture media. Model simulations accurately predicted multicellular Vmem patterns when one or more molecular components were altered, as quantitatively confirmed by a machine learning-based quantitative image pattern similarity analysis. In the second modeling analysis, a genome-scale computational model of the human metabolic network was expanded with additional descriptors to investigate how induced pluripotent stem cells reroute metabolic fluxes and achieved cell growth objectives during cardiomyocyte differentiation under various culture media compositions. This framework integrated transcriptomic, thermodynamic, kinetic, and proteomic and novel fluxosome constraints including transport exchange between the cytosol and extracellular environment. From a comparative analysis across multiple published studies and our own experimental validations, we observed that the combination of novel and previous model constraints was required to replicate experimental media-induced changes in metabolic network dynamics during pluripotency and hiPSC-cardiomyocyte (hiPSC-CM) differentiation. We extended this study to a novel media supplementation condition of glutamine and ascorbic acid and found that experimental extracellular flux assays supported the model-predicted improvements to metabolic respiration of iPSC-derived cardiomyocyte progenitor cells. In summary, these results collectively validate the potential for model-guided media design of engineered living systems using understanding of bioelectric and metabolic systems properties.